1. Field of the Invention
Generally, the present disclosure relates to manufacturing processes, and, more particularly, to the assessment of a manufacturing environment, such as a semiconductor facility, in which a plurality of different product types and process and metrology tools are supplied with products on the basis of an automated material handling system (AMHS).
2. Description of the Related Art
Today's global market forces manufacturers of mass products to offer high quality products at a low price. It is thus important to improve yield and process efficiency to minimize production costs. This holds especially true in industrial fields in which highly complex process tools operate on complex products according to specified process parameters that may vary between different product types. A prominent example in this respect represents the field of semiconductor fabrication since, here, it is essential to combine cutting-edge technology with mass production techniques. It is, therefore, the goal of semiconductor manufacturers to reduce the consumption of raw materials and consumables while at the same time improve process tool utilization. The latter aspect is especially important since, in modern semiconductor facilities, the equipment that is required is extremely cost intensive and represents the dominant part of the total production costs.
Integrated circuits are one example of a mass-produced product that is typically manufactured in automated or semi-automated facilities, thereby passing through a large number of process and metrology steps to complete the device. The number and the type of process steps and metrology steps a product, such as a semiconductor device, has to go through depends on the specifics of the product to be fabricated. For example, a typical process flow for an integrated circuit may include a plurality of photolithography steps to image a circuit pattern for a specific device layer into a resist layer, which is subsequently patterned to form a resist mask for further processes for structuring the device layer under consideration by, for example, etch or implant processes, deposition processes, heat treatments, cleaning processes and the like. Thus, layer after layer, a plurality of process steps are performed based on a specific lithographic mask set for the various layers of the specified device. For instance, a sophisticated CPU requires several hundred process steps, each of which has to be carried out within specified process margins so as to fulfill the specifications for the device under consideration. As the majority of the process margins are device-specific, many of the metrology processes and the actual manufacturing processes are specifically designed for the device under consideration and require specific parameter settings at the adequate metrology and process tools.
In many production plants, such as semiconductor facilities, a plurality of different product types are usually manufactured at the same time, such as memory chips of different design and storage capacity, CPUs of different design and operating speed and the like, wherein the number of different product types may even reach a hundred and more in production lines for manufacturing ASICs (application specific ICs). Since each of the different product types may require a specific process flow, specific settings in the various process tools, such as different mask sets for the lithography, different process parameters for deposition tools, etch tools, implantation tools, chemical mechanical polishing (CMP) tools, furnaces and the like, may be necessary. Consequently, a plurality of different tool parameter settings and product types may be encountered simultaneously in a manufacturing environment. As a consequence, passing the various product types through the plurality of process tools requires a complex scheduling regime to ensure high product quality and achieve a high performance, such as a high overall throughput of the process tools to obtain a maximum number of products per time and per tool investment costs. Hence, the tool performance, especially in terms of throughput, is a very critical manufacturing parameter as it significantly affects the overall production costs of the individual products. Therefore, in the field of semiconductor production, various strategies are practiced in an attempt to optimize the stream of products for achieving a high yield with moderate consumption of raw materials.
In semiconductor plants, substrates are usually handled in groups, called lots, which are, depending on the degree of automation, conveyed within the manufacturing environment by an automated transport system, also referred to as automated material handling system (AMHS), delivering the substrates in corresponding carriers to so-called load ports of the tools and picking up carriers therefrom that contain previously processed substrates. Thus, the transport process itself may represent an important factor for efficiently scheduling and managing the manufacturing environment, since the time for loading and unloading carriers may take up to several minutes per carrier exchange event and may be subjected to a great variance, which may result in unwanted idle times at specific process tools, thereby reducing the performance thereof. On the other hand, process tools are increasingly used that integrate more and more functions which may lead to increased cycle times in the process tools. Due to the increased cycle times, possibly in combination with a highly varying lot size encountered in the manufacturing environment due to the large number of different product types that may be processed on demand, the available time for carrier exchange at load ports of process tools may decrease. However, since the variability of the carrier exchange times (CETs) may be high, a significant influence of the transport status in the manufacturing environment on the overall productivity may be observed. Thus, when designing or redesigning a manufacturing environment, for instance by installing new or additional equipment, the tool characteristics with respect to transport capabilities, such as the number of load ports for specific tools and the like, and the capabilities and operational behavior of the AMHS may represent important factors for the performance of the manufacturing environment as a whole.
Thus, in some conventional techniques, it is attempted to assess the influence of the transport capabilities on the overall behavior of the manufacturing environment on the basis of simulation models in order to determine possible tools exhibiting a pronounced dependence on the characteristics of the AMHS. However, this approach requires detailed simulation models that may have to be established under high efforts, while the results of the corresponding calculations may be subjected to uncertainties and variances as are typically associated with simulation models.
In view of the situation described above, there is therefore a need for a technique for more efficiently assessing transport-related issues in a manufacturing environment while avoiding or reducing one or more of the problems identified above.